MétaCan
Menu
Back to cohort
Record W2095672860 · doi:10.1109/iembs.1990.692216

Muscle Contraction Interference In Acceleration Vibroarthrography

2005· article· en· W2095672860 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaArthritis Society
KeywordsContraction (grammar)Interference (communication)Biomedical engineeringComputer scienceAccelerationVibrationSIGNAL (programming language)Articular cartilageAcousticsMedicinePhysicsInternal medicinePathologyTelecommunicationsOsteoarthritis

Abstract

fetched live from OpenAlex

Vibroarthrography (VAG) is a noninvasive technique to detect vibration signals from the knee joint for the diagnosis of articular cartilage diseases. To improve the quality of VAG signals and to extract relevant information from them, possible sources of artifacts such as muscle contraction interference (MCI) were investigated by using a multi-channelvibration detection system. Analysis of the signals indicates that signal power and median frequency of VAG signals are affected by MCI. Our findings suggest that monitoring and reduction of MCI is necessary in order for vibroarthrography to be clinically useful.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.224
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations10
Published2005
Admission routes2
Has abstractyes

Explore more

Same topicNon-Invasive Vital Sign MonitoringFrench-language works237,207